Research output per year
Research output per year
Personal profile
Research Interests
Professor Wang's interests are differential privacy, privacy-preserving machine learning, privacy-preserving data mining, privacy attack in machine learning, trustworthy machine learning, statistical learning theory. He is also interested in trustworthy issues in digital healthcare, biomedical imaging and bioinformatics.
Education
Ph.D., CRF CRG5 The State University of New York at Buffalo
2020
M.S., Western University
2015
B.S, Shandong University
2014
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Gradient complexity and non-stationary views of differentially private empirical risk minimization
Wang, D. & Xu, J., Jan 8 2024, In: Theoretical Computer Science. 982, 114259.Research output: Contribution to journal › Article › peer-review
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PAC learning halfspaces in non-interactive local differential privacy model with public unlabeled data
Su, J., Xu, J. & Wang, D., May 2024, In: Journal of Computer and System Sciences. 141, 103496.Research output: Contribution to journal › Article › peer-review
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Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI
Zhou, J., Zhou, L., Wang, D., Xu, X., Li, H., Chu, Y., Han, W. & Gao, X., Feb 2024, In: Computers in Biology and Medicine. 169, 107861.Research output: Contribution to journal › Article › peer-review
4 Scopus citations -
A Fundamental Model with Stable Interpretability for Traffic Forecasting
Gou, X., Hu, L., Wang, D. & Zhang, X., Nov 13 2023, GeoPrivacy 2023 - Proceedings of the 1st ACM SIGSPATIAL International Workshop on GeoPrivacy and Data Utility for Smart Societies. Association for Computing Machinery, Inc, p. 10-13 4 p. (GeoPrivacy 2023 - Proceedings of the 1st ACM SIGSPATIAL International Workshop on GeoPrivacy and Data Utility for Smart Societies).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction
Xiao, H., Xiang, Z., Wang, D. & Devadas, S., Jul 21 2023, 2023 IEEE Symposium on Security and Privacy (SP). IEEEResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution
5 Scopus citations -
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards
Wu, Y., Zhou, X., Chowdhury, S. R. & Wang, D., 2023, p. 37880-37918. 39 p.Research output: Contribution to conference › Paper › peer-review
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Differentially Private Stochastic Convex Optimization in (Non)-Euclidean Space Revisited
Su, J., Zhao, C. & Wang, D., Mar 31 2023, 39th Conference on Uncertainty in Artificial Intelligence, UAI 2023. ML Research Press, p. 2026-2035 10 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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EEFL: High-Speed Wireless Communications Inspired Energy Efficient Federated Learning over Mobile Devices
Chen, R., Wan, Q., Zhang, X., Qin, X., Hou, Y., Wang, D., Fu, X. & Pan, M., Jun 18 2023, Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services. ACMResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations
Press/Media
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Aalto University Researcher Details New Studies and Findings in the Area of Hydrocarbons (Rheological Behaviors of Waste Polyethylene Modified Asphalt Binder: Statistical Analysis of Interlaboratory Testing Results)
08/7/24
1 item of Media coverage
Press/Media: Press / Media
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New Google collaboration advances AI research in Saudi Arabia
Al-Naffouri, T., Gao, X., Ghanem, B., Elhoseiny, M., Wang, D. & Setti, G.
07/8/24
1 item of Media coverage
Press/Media: Press / Media
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Researchers at King Abdullah University of Science and Technology (KAUST) Report New Data on Technology (Pac Learning Halfspaces In Non-interactive Local Differential Privacy Model With Public Unlabeled Data)
05/6/24
1 item of Media coverage
Press/Media: Press / Media
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Findings on Machine Learning Discussed by Investigators at King Abdullah University of Science and Technology (KAUST) (Ppml-omics: a Privacy-preserving Federated Machine Learning Method Protects Patients' Privacy In Omic Data)
Gao, X., Han, W., Li, Z., Zhou, L., Zhang, B., Wang, D., Zhou, J., Chen, S. & Wu, Y.
05/3/24
1 item of Media coverage
Press/Media: Press / Media
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Recent Findings from Xinjiang University Highlight Research in Applied Sciences (Numerical Analysis of the Wing Leading Edge Electro-Impulse De-Icing Process Based on Cohesive Zone Model)
04/16/24
1 item of Media coverage
Press/Media: Press / Media
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Reports from King Abdullah University of Science and Technology (KAUST) Provide New Insights into CDC and FDA (Personalized and Privacy-preserving Federated Heterogeneous Medical Image Analysis With Pppml-hmi)
Gao, X., Han, W., Zhou, L., Wang, D., Zhou, J., Xu, X. & Chu, Y.
02/20/24
1 item of Media coverage
Press/Media: Press / Media
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New Information Technology Data Have Been Reported by Researchers at King Abdullah University of Science and Technology (KAUST) (Generalized Linear Models In Non-interactive Local Differential Privacy With Public Data)
01/24/24
1 item of Media coverage
Press/Media: Press / Media
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Researchers from Aalto University Publish Research in Civil Engineering (Fabrication and characterization of multiphase bituminous materials for cold region pavements)
11/15/23
1 item of Media coverage
Press/Media: Press / Media